In some countries, businesses may require making unofficial payments or gifts to "get things done." The indicators below capture the prevalence of different types of bribery in 135 countries. The results are based on surveys of more than 130,000 firms. A database query tool is available to help you better understand the prevalence of corruption across various firm subgroups. You can also generate graphs to compare countries.

To see the details for a specific economy, click on the links below. Click on column headers to sort data.

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Custom Data Set

Generate a Custom Data Set for Corruption including standard errors, indicator values by firm subgroups, historical data and selected countries.

VIEWING INDICATORS

Percent of firms expected to give gifts to public officials "to get things done" Percent of establishments that consider that firms with characteristics similar to theirs are making informal payments or giving gifts to public officials to "get things done” with regard to customs, taxes, licenses, regulations, services, etc.
Percent of firms expected to give gifts in meetings with tax officialsPercent of firms expected to give gifts or an informal payment in meetings with tax officials.
Percent of firms expected to give gifts to secure government contractPercent of establishments that consider that firms with characteristics similar to theirs are making informal payments or giving gifts to public officials to secure government contract.
Value of gift expected to secure a government contract (% of contract value)Percentage of the contract value expected as a gift to secure a government contract. Only firms that have confirmed that they have secured or attempted to secure a government contract in the last 12 months were required to answer this question.
Percent of firms expected to give gifts to get an operating licensePercent of firms expected to give gifts or an informal payment to get an operating license.
Percent of firms expected to give gifts to get an import license Percent of firms expected to give gifts or an informal payment to get an import license.
World24.814.222.92.214.513.3
East Asia & Pacific21.013.324.23.112.215.0
Eastern Europe & Central Asia22.912.517.61.612.614.4
Latin America & Caribbean10.96.19.90.98.45.7
Middle East & North Africa50.047.948.65.142.551.1
South Asia35.627.828.51.614.413.5
Sub-Saharan Africa34.918.233.83.219.816.1
Afghanistan (2008)41.528.843.02.816.524.1
Albania (2007)57.722.430.53.210.921.8
Algeria (2007)66.615.034.84.17.334.9
Angola (2010)48.934.258.59.839.055.6
Antigua and Barbuda (2010)4.86.1003.94.3
Argentina (2010)18.18.710.30.73.37.0
Armenia (2009)16.013.30.6011.36.2
Azerbaijan (2009)52.243.214.21.134.627.7
Bahamas, The (2010)19.110.90017.89.4
Bangladesh (2007)85.154.426.71.232.451.3
Barbados (2010)14.71.64.10.17.90
Belarus (2008)26.16.37.10.411.70
Belize (2010)3.06.70000
Benin (2009)54.526.859.05.044.624.4
Bhutan (2009)10.12.57.00.31.40
Bolivia (2010)17.63.423.32.33.44.8
Bosnia and Herzegovina (2009)10.31.50.606.09.4
Botswana (2010)7.38.41.00.12.95.0
Brazil (2009)11.916.40.705.41.2
Bulgaria (2009)22.46.62.6016.823.9
Burkina Faso (2009)8.56.711.80.94.117.8
Burundi (2006)56.522.644.44.440.320.9
Cambodia (2007)61.260.376.814.9...43.9
Cameroon (2009)51.230.858.86.039.626.2
Cape Verde (2009)6.01.10002.3
Central African Republic (2011)41.816.840.84.35.86.3
Chad (2009)41.821.247.34.352.628.1
Chile (2010)0.70.40.701.20.3
Colombia (2010)2.81.532.82.62.90.3
Congo, Dem. Rep. (2010)65.754.475.79.353.87.8
Congo, Rep. (2009)81.837.149.93.7n.a.21.1
Costa Rica (2010)3.77.60.209.30
Côte d'Ivoire (2009)38.513.628.53.231.828.5
Croatia (2007)14.56.04.30.22.10.1
Czech Republic (2009)12.80.219.21.50.20
Dominica (2010)05.6001.63.7
Dominican Republic (2010)10.115.314.40.713.636.7
Ecuador (2010)11.80.42.30.31.41.1
Egypt, Arab Rep. (2008)15.25.332.01.213.420.0
El Salvador (2010)12.70.35.80.62.10.3
Eritrea (2009)000000
Estonia (2009)3.700000
Ethiopia (2011)4.03.82.70.213.50.7
Fiji (2009)10.24.53.001.22.4
Gabon (2009)41.822.826.61.400
Gambia, The (2006)52.413.650.34.323.429.0
Georgia (2008)14.78.4003.542.6
Germany (2005)...14.8............
Ghana (2007)38.818.161.28.322.638.8
Greece (2005)21.655.914.50.8......
Grenada (2010)7.11.97.20.37.75.5
Guatemala (2010)6.33.99.91.25.00.3
Guinea (2006)84.857.374.67.951.934.3
Guinea-Bissau (2006)63.122.743.42.815.316.7
Guyana, CR (2010)18.44.60011.411.4
Honduras (2010)6.12.814.91.34.10.3
Hungary (2009)5.40.7002.63.6
India (2006)47.552.323.81.052.546.0
Indonesia (2009)14.914.038.11.825.919.5
Iraq (2011)31.829.131.01.824.241.0
Ireland (2005)8.311.07.70.2......
Jamaica (2010)17.914.30.8019.027.9
Jordan (2006)18.10.92.30.13.11.3
Kazakhstan (2009)34.025.144.95.230.036.6
Kenya (2007)79.232.371.07.828.818.6
Korea, Rep. (2005)14.121.325.80.2......
Kosovo (2009)7.57.79.91.05.80.8
Kyrgyz Republic (2009)47.839.053.04.725.723.2
Lao PDR (2012)35.823.144.53.318.529.4
Latvia (2009)13.44.445.54.200
Lebanon (2009)22.919.297.78.812.50
Lesotho (2009)28.19.216.70.63.31.7
Liberia (2009)55.454.451.63.549.646.0
Lithuania (2009)10.73.412.20.45.40.3
Macedonia, FYR (2009)16.98.10.202.93.8
Madagascar (2009)21.86.88.90.218.64.8
Malawi (2009)10.811.42.80.13.50
Malaysia (2007)..................
Mali (2010)19.420.222.82.542.435.2
Mauritania (2006)82.148.276.28.133.232.8
Mauritius (2009)5.90.38.80.200.9
Mexico (2010)11.610.433.74.517.51.0
Micronesia, Fed. Sts. (2009)000000
Moldova (2009)33.515.518.11.47.46.7
Mongolia (2009)33.420.838.93.231.323.1
Montenegro (2009)9.33.419.81.62.00
Morocco (2007)13.410.76.40.3020.0
Mozambique (2007)14.89.831.62.46.910.6
Namibia (2006)11.42.68.10.500
Nepal (2009)15.214.962.24.411.73.3
Nicaragua (2010)8.34.24.50.45.00.3
Niger (2009)35.213.743.43.932.53.7
Nigeria (2007)40.922.944.34.740.333.3
Pakistan (2007)48.058.814.10.312.70
Panama (2010)30.56.4n.a.n.a.8.57.4
Paraguay (2010)17.514.621.71.732.08.9
Peru (2010)21.48.426.31.612.40.9
Philippines (2009)18.621.858.516.410.619.4
Poland (2009)14.74.89.80.81.436.3
Portugal (2005)14.552.127.60.6......
Romania (2009)22.212.112.81.125.825.1
Russian Federation (2012)20.57.320.72.512.627.5
Rwanda (2011)6.34.46.80.302.5
Samoa (2009)29.319.614.41.915.416.1
Senegal (2007)18.118.736.33.021.18.6
Serbia (2009)21.43.65.90.309.0
Sierra Leone (2009)20.48.633.93.88.72.8
Slovak Republic (2009)15.73.140.85.300.5
Slovenia (2009)5.800006.5
South Africa (2007)15.13.132.21.702.7
Spain (2005)4.414.32.40.1......
Sri Lanka (2011)13.77.718.20.412.02.5
St. Kitts and Nevis (2010)6.1010.00.41.20
St. Lucia (2010)0.411.9005.80
St. Vincent and the Grenadines (2010)2.85.90010.14.3
Suriname (2010)8.01.80000
Swaziland (2006)40.63.331.91.17.317.6
Syrian Arab Republic (2009)83.861.066.47.225.225.2
Tajikistan (2008)44.633.026.62.038.531.5
Tanzania (2006)49.514.742.22.920.16.6
Thailand (2006)..................
Timor-Leste (2009)19.42.616.83.15.011.6
Togo (2009)16.716.45.50.315.725.7
Tonga (2009)12.71.4005.021.1
Trinidad and Tobago (2010)13.45.56.80.543.516.7
Turkey (2008)18.04.023.12.310.70.3
Uganda (2006)51.714.545.55.612.923.9
Ukraine (2008)31.828.338.53.737.32.6
Uruguay (2010)8.11.8000.80
Uzbekistan (2008)59.552.448.92.558.970.5
Vanuatu (2009)4.34.68.81.56.54.3
Venezuela, R.B. (2010)23.66.465.59.04.023.4
Vietnam (2009)52.533.743.72.515.218.2
West Bank and Gaza (2006)13.32.74.70.51.62.9
Yemen, Rep. (2010)68.266.766.28.360.861.1
Zambia (2007)14.34.927.42.12.66.4
Zimbabwe (2011)7.212.63.70.15.310.4

Notes

* This indicator is computed using data from manufacturing firms only.

Additional Notes

  1. Most surveys were administered using the Enterprise Surveys Global Methodology as outlined in the Methodology page, while some others did not strictly adhere to the Enterprise Surveys Global Methodology. For example, the Universe under consideration may have consisted of only manufacturing firms or the questionnaire used may have been different from the standard global questionnaire. Data users should exercise caution when comparing raw data and point estimates between surveys that did and did not adhere to the Enterprise Surveys Global Methodology. For surveys which did not adhere to the Global Methodology plus Afghanistan, any inference from one of these surveys is representative only for the data sample itself.
  2. Regional and world averages of indicators are computed by taking a simple average of country-level point estimates. For each economy, only the latest available year of survey data is used in this computation. Only surveys adhering to the Enterprise Surveys Global Methodology are used to compute these regional and world averages.
  3. Descriptions of firm subgroup levels, e.g. how the ex post groupings are constructed, are provided in the Indicator Descriptions (PDF, 710KB) document.
  4. Statistics derived from less than five firms are displayed with an "n.a." to maintain confidentiality and should be distinguished from ".." which indicates missing values.
  5. Standard errors are labeled "n.c.", meaning not computed, for the following:
           1) indicators for all surveys that were not conducted using the Enterprise Surveys Global Methodology and
           2) for indicator breakdowns by ex post groupings: exporter or ownership type, and gender of the top manager.
  6. Please cite our data as follows:
    Enterprise Surveys (http://www.enterprisesurveys.org), The World Bank.